测风塔风速的长程持续性特征研究
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国家气象科技创新工程(CMAGGTD0035)、新疆气象科技发展基金重点项目(ZD202304)、第三次新疆综合科学考察项目(2021xjkk1300)共同资助


Research on Long-Range Persistence of Tower Wind Speed Based on DFA Method
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    摘要:

    基于中国陆上风能资源专业观测网提供的测风塔风速资料,本文利用去趋势波动分析(Detrended Fluctuation Analysis, DFA)方法,研究了103座测风塔在不同高度处观测的、不同分辨率的风速时间序列的长程持续性特征。结果表明:①同一测风塔观测的不同高度处的风速时间序列,存在一致的标度行为,与数据时间分辨率无关;②对于6 h平均风速序列而言,103座测风塔观测风速的DFA指数α数值范围基本在0.55~0.91之间,都表现出较强的长程持续性,区域特征不明显;③对于10 min平均风速序列,DFA标度指数曲线存在弯折,以24 h尺度为界,呈现出2个明显的独立标度区间:在较大的时间尺度上,标度指数α的数值大小为0.80,而在较小的时间尺度上,α的数值大小约为1.38。

    Abstract:

    Based on the Detrended Fluctuation Analysis (DFA) method, this paper focuses on the longrange correlation characteristics of wind speed time series observed by 103 wind measuring towers. The results show that: (1) The wind speed time series at different heights have almost consistent scale behaviour, regardless of the resolution. (2) For the 6hour average wind speed series, the DFA index α has a numerical range basically of 0.55 to 0.91 for all 103 wind towers, showing strong longrange persistence. (3) For the 10minute average wind speed series, taking the 24hour scale as the boundary, the DFA curve shows two obvious independent scaling intervals: on the larger time scale, the numerical size of scaling index α is 0.80, while α is about 1.38 on the smaller time scale. This study quantifies the longrange persistence characteristics of wind speed using the nonlinear time series analysis method. It reveals the physical mechanism behind it, which is of great significance for building wind speed models and accurately predicting wind speed.

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李庆雷,陈丽凡,张志森,刘卫平.测风塔风速的长程持续性特征研究[J].气象科技,2023,51(2):262~268

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  • 收稿日期:2021-10-18
  • 定稿日期:2022-11-21
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  • 在线发布日期: 2023-04-27
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